排序方式： 共有15条查询结果，搜索用时 312 毫秒
1.
This study examined whether or not activity monitor data collected as part of a typical 7-day physical activity (PA) measurement protocol can be expected to be missing at random. A total of 315 participants (9–18 years) each wore a SenseWear Armband monitor for 7 consecutive days. Participants were classified as “compliant” (86 boys and 124 girls) if they had recorded accelerometer data during 70% or more of the predefined awake time (7 AM–10 PM) on four different days; and “non-compliant” (44 boys and 51 girls) when not meeting these criteria. Linear mixed models were used to examine differences in energy expenditure (EE) levels by compliance across 10 different time periods. The results indicated that non-compliant girls were older (13.4 ± 2.9 vs. 12.2 ± 2.5) and taller (156.8 ± 10.3 vs. 152.8 ± 11.3) than their same gender compliant peers (P < .05). Comparisons of EE rates at segmented portions of the day revealed no differences between compliant and non-compliant groups (P ≥ .05). Differences in EE ranged from ?0.32 kcal · kg?1 · h?1 (before school time) to 0.62 kcal · kg?1 · h?1 (physical education class) in boys and ?0.39 kcal · kg?1 · h?1 (transportation from school) to 0.37 kcal · kg?1 · hour?1 (recess) in girls. The results showed that compliant and non-compliant individuals differed in a few demographic characteristics but exhibited similar activity patterns. This suggests that data were considered to be missing at random, but additional work is needed to confirm this observation in a representative sample of children using other types of activity monitors and protocols. 相似文献
2.
3.
The purpose of this study was to determine the validity of the metabolic equivalent (MET) equation and step rate function of the ActivPAL? physical activity logger in a group of females. Using a standard treadmill protocol, 62 females aged 15-25 years walked on a treadmill at speeds between 3.2 and 7.0 km · h(-1) while wearing an ActivPAL. Oxygen consumption was measured using expired gas analysis at each speed and METs for each speed were estimated based on each participant's own resting metabolic rate. A sub-set of 18 participants also wore an Actigraph. Results showed that the in-built equation in the ActivPAL significantly underestimated (P < 0.001) METs under treadmill conditions at higher intensities. The ActivPAL equation is based on step rate yet the relationship between counts and measured METs (r = 0.76; P < 0.001) is stronger than that between steps and measured METs (r = 0.59; P < 0.001). Both the ActivPAL and Actigraph step functions showed no significant difference (P > 0.05) to video recorded step rate except at the slowest walking speed where the Actigraph significantly underestimated steps (P < 0.05). The development of a new equation based on the counts-METs relationship that includes a variety of speeds and activities would be useful. The ActivPAL step function performs better than the Actigraph at the slowest walking speed under treadmill conditions. 相似文献
4.
Yang Bai Paul Hibbing Constantine Mantis Gregory J. Welk 《Journal of sports sciences》2018,36(15):1734-1741
The purpose of this investigation was to examine the validity of energy expenditure (EE), steps, and heart rate measured with the Apple Watch 1 and Fitbit Charge HR. Thirty-nine healthy adults wore the two monitors while completing a semi-structured activity protocol consisting of 20 minutes of sedentary activity, 25 minutes of aerobic exercise, and 25 minutes of light intensity physical activity. Criterion measures were obtained from an Oxycon Mobile for EE, a pedometer for steps, and a Polar heart rate strap worn on the chest for heart rate. For estimating whole-trial EE, the mean absolute percent error (MAPE) from Fitbit Charge HR (32.9%) was more than twice that of Apple Watch 1 (15.2%). This trend was consistent for the individual conditions. Both monitors accurately assessed steps during aerobic activity (MAPEApple: 6.2%; MAPEFitbit: 9.4%) but overestimated steps in light physical activity. For heart rate, Fitbit Charge HR produced its smallest MAPE in sedentary behaviors (7.2%), followed by aerobic exercise (8.4%), and light activity (10.1%). The Apple Watch 1 had stronger validity than the Fitbit Charge HR for assessing overall EE and steps during aerobic exercise. The Fitbit Charge HR provided heart rate estimates that were statistically equivalent to Polar monitor. 相似文献
5.
The Validity of the Tritrac-R3D Activity Monitor for the Assessment of Physical Activity in Children
Abstract The purpose of this study was to evaluate the validity of the Tritrac-R3D Activity Monitor, a new instrument designed to improve assessments of physical activity. Comparisons were made with a heart rate monitor and with a Caltrac Activity Monitor. Thirty-five children (ages 9–11 years) were monitored on 3 different school days with all 3 instruments. The Tritrac was moderately correlated with the heart rate monitor (r =.58) and highly correlated with the Caltrac monitor (r =.88). By taking advantage of the minute-by-minute timing capability of the Tritrac and the heart rate monitors, it was discovered, that the correlations between these instruments were highest during free play situations (lunch/recess, recess, after school) and were lower when activity was more limited (class time) or structured (physical education). The ability of the Tritrac to assess activity on a minute-by-minute basis may greatly enhance its overall utility. 相似文献
6.
Pedro Silva Jorge Mota Dale Esliger Gregory Welk 《Measurement in physical education and exercise science》2013,17(2):79-91
The purpose of this study was to determine the reliability of the Actigraph GT1M (Pensacola, FL, USA) accelerometer activity count and step functions. Fifty GT1M accelerometers were initialized to collect simultaneous acceleration counts and steps data using 15-sec epochs. All reliability testing was completed using a mechanical shaker plate to perform six different test conditions in Experiment 1 and 18 test conditions in Experiment 2. The overall intra- and inter-instrument reliability of the GT1M was CVintra = 2.9% and CVinter = 3.5% for counts and CVintra = 1.1% and CVinter = 1.2% for steps. No batch effects were evident in the 50 GT1Ms. The Actigraph GT1M accelerometer demonstrated good reliability for measuring both counts and steps. However, the ability of the GT1M to consistently detect acceleration at a given acceleration and frequency condition varied widely. Future studies clarifying the filtering limitations and the threshold necessary to detect the occurrence of movement are warranted. 相似文献
7.
Robert J. Noonan Danielle Christian Lynne M. Boddy Pedro F. Saint-Maurice Gregory J. Welk Paul R. Hibbing 《Journal of sports sciences》2019,37(16):1919-1925
This study used accelerometer and self-report measures of overall sedentary time (ST) and screen time behaviours to examine their respective associations with adiposity among UK youth. Participants (Year groups 5, 8, and 10; n=292, 148 girls) wore the SenseWear Armband Mini accelerometer for eight days and completed the Youth Activity Profile, an online report tool designed to estimate physical activity and ST.Stature, body mass and waist circumference were measured to classify adiposity outcomes (overweight/obese and central obesity). One-way between groups ANOVA and adjusted linear, logistic and multinomial logistic regression analyses were conducted. There was a significant main effect of age on total ST across the whole week (F(2, 289)=41.64, p≤0.001). ST increased monotonically across Year 5 (581.09±107.81 min·dˉ¹), 8 (671.96±112.59 min·dˉ¹) and 10 (725.80±115.20 min·dˉ¹), and all pairwise comparisons were significant at p≤0.001. A steep age-related gradient to mobile phone use was present (p≤0.001). ST was positively associated with adiposity outcomes independent of moderate-to-vigorous intensity physical activity (MVPA; p≤0.001). Engaging in >3 hours of video gaming daily was positively associated with central obesity (OR=2.12, p≤0.05) but not after adjustment for MVPA. Results further demonstrate the importance of reducing overall ST to maintain healthy weight status among UK youth. 相似文献
8.
Hyun-Sung An Gregory C. Jones Seoung-Ki Kang Gregory J. Welk 《European Journal of Sport Science》2017,17(3):360-368
Wearable activity trackers have become popular for tracking individual’s daily physical activity, but little information is available to substantiate the validity of these devices in step counts. Thirty-five healthy individuals completed three conditions of activity tracker measurement: walking/jogging on a treadmill, walking over-ground on an indoor track, and a 24-hour free-living condition. Participants wore 10 activity trackers at the same time for both treadmill and over-ground protocol. Of these 10 activity trackers three were randomly given for 24-hour free-living condition. Correlations of steps measured to steps observed were r?=?0.84 and r?=?0.67 on a treadmill and over-ground protocol, respectively. The mean MAPE (mean absolute percentage error) score for all devices and speeds on a treadmill was 8.2% against manually counted steps. The MAPE value was higher for over-ground walking (9.9%) and even higher for the 24-hour free-living period (18.48%) on step counts. Equivalence testing for step count measurement resulted in a significant level within ±5% for the Fitbit Zip, Withings Pulse, and Jawbone UP24 and within ±10% for the Basis B1 band, Garmin VivoFit, and SenseWear Armband Mini. The results show that the Fitbit Zip and Withings Pulse provided the most accurate measures of step count under all three different conditions (i.e. treadmill, over-ground, and 24-hour condition), and considerable variability in accuracy across monitors and also by speeds and conditions. 相似文献
9.
Pedro F. Saint-Maurice Gregory J. Welk R. Todd Bartee Kate Heelan 《Journal of sports sciences》2017,35(9):866-872
This study tests calibration models to re-scale context-specific physical activity (PA) items to accelerometer-derived PA. A total of 195 4th–12th grades children wore an Actigraph monitor and completed the Physical Activity Questionnaire (PAQ) one week later. The relative time spent in moderate-to-vigorous PA (MVPA%) obtained from the Actigraph at recess, PE, lunch, after-school, evening and weekend was matched with a respective item score obtained from the PAQ’s. Item scores from 145 participants were calibrated against objective MVPA% using multiple linear regression with age, and sex as additional predictors. Predicted minutes of MVPA for school, out-of-school and total week were tested in the remaining sample (n = 50) using equivalence testing. The results showed that PAQ β-weights ranged from 0.06 (lunch) to 4.94 (PE) MVPA% (P < 0.05) and models root mean square error ranged from 4.2% (evening) to 20.2% (recess). When applied to an independent sample, differences between PAQ and accelerometer MVPA at school and out-of-school ranged from ?15.6 to +3.8 min and the PAQ was within 10–15% of accelerometer measured activity. This study demonstrated that context-specific items can be calibrated to predict minutes of MVPA in groups of youth during in- and out-of-school periods. 相似文献
10.
Dzewaltowski DA Karteroliotis K Welk G Johnston JA Nyaronga D Estabrooks PA 《运动与训练心理学杂志》2007,29(3):310-332
This study developed youth self-efficacy (SEPA) and proxy efficacy (PEPA) measures for physical activity (PA). Proxy efficacy was defined as a youth's confidence in his or her skills and abilities to get others to act in one's interests to create supportive environments for PA. Each spring of their sixth-, seventh-, and eighth-grade years, middle school students completed SEPA and PEPA questions and then, for 3 days, recalled their previous day's after-school PA. Exploratory and confirmatory factor analyses revealed a four-factor structure (SEPA for 1-3 days, SEPA for 5-7 days, PEPA-Parents, PEPA-School). Across study years, SEPA 1-3 days and 5-7 days increased and PEPA-Parents and PEPA-School decreased. Initial levels of PEPA-Parents and SEPA scales were associated with initial levels of PA. From sixth through seventh grade, changes in SEPA scales were associated with changes in PA. Studies should test whether interventions targeting self-efficacy and proxy efficacy influence PA. 相似文献